Open Access
Space mission risk, sustainability and supply chain: review, multi-objective optimization model and practical approach
(MDPI, 2023) Sawik, Bartosz; Estadística, Informática y Matemáticas; Estatistika, Informatika eta Matematika; Institute of Smart Cities - ISC; Universidad Pública de Navarra / Nafarroako Unibertsitate Publikoa
This paper investigates the convergence of risk, sustainability, and supply chain in space missions, including a review of fundamental concepts, the introduction of a multi-objective conceptual optimization model, and the presentation of a practical approach. Risks associated with space missions include technical, human, launch, space environment, mission design, budgetary, and political risks. Sustainability considerations must be incorporated into mission planning and execution to ensure the long-term viability of space exploration. The study emphasizes the importance of considering environmental sustainability, resource use, ethical concerns, long-term planning, international collaboration, and public outreach in space missions. It emphasizes the significance of reducing negative environmental consequences, increasing resource use efficiency, and making responsible and ethical actions. The paper offers a multi-objective optimization conceptual model that may be used to evaluate and choose sustainable space mission tactics. This approach considers a variety of elements, including environmental effects, resource utilization, mission cost, and advantages for society. It provides a systematic decision-making approach that examines trade-offs between different criteria and identifies optimal conceptual model solutions that balance risk, sustainability, and supply chain objectives. A practical approach is also offered to demonstrate the use of the multi-criteria optimization conceptual model in a space mission scenario. The practical approach demonstrates how the model can aid in the development of mission strategies that minimize risks, maximize resource consumption, and fit with sustainability goals. Overall, this paper delivers a multi-criteria optimization conceptual model and provides a space mission planning practical approach, as well as an overview of the interaction between risk, sustainability, and supply chain in space mission organization, planning, and execution.
Open Access
Optimizing last-mile delivery: a multi-criteria approach with automated smart lockers, capillary distribution and crowdshipping
(MDPI, 2024) Sawik, Bartosz; Estadística, Informática y Matemáticas; Estatistika, Informatika eta Matematika
Background: This publication presents a review, multiple criteria optimization models, and a practical example pertaining to the integration of automated smart locker systems, capillary distribution networks, crowdshipping, last-mile delivery and supply chain management. This publication addresses challenges in logistics and transportation, aiming to enhance efficiency, reduce costs and improve customer satisfaction. This study integrates automated smart locker systems, capillary distribution networks, crowdshipping, last-mile delivery and supply chain management. Methods: A review of the existing literature synthesizes key concepts, such as facility location problems, vehicle routing problems and the mathematical programming approach, to optimize supply chain operations. Conceptual optimization models are formulated to solve the complex decisionmaking process involved in last-mile delivery, considering multiple objectives, including cost minimization, delivery time optimization, service level minimization, capacity optimization, vehicle minimization and resource utilization. Results: The multiple criteria approaches combine the vehicle routing problem and facility location problem, demonstrating the practical applicability of the proposed methodology in a real-world case study within a logistics company. Conclusions: The execution of multi-criteria models optimizes automated smart locker deployment, capillary distribution design, crowdshipping and last-mile delivery strategies, showcasing its effectiveness in the logistics sector.
Open Access
Multi-criteria optimization for fleet size with environmental aspects
(Elsevier, 2017) Sawik, Bartosz; Faulín Fajardo, Javier; Pérez Bernabeu, Elena; Institute of Smart Cities - ISC
This research concerns multi-criteria vehicle routing problems. Mathematical models are formulated with mixed-integer programming. We consider maximization of capacity of truck vs. minimization of utilization of fuel, carbon emission and production of noise. The problems deal with green logistics for routes crossing the Western Pyrenees in Navarre, Basque Country and La Rioja, Spain.We consider heterogeneous fleet of trucks. Different types of trucks have not only different capacities, but also require different amounts of fuel for operations. Consequently, the amount of carbon emission and noise vary as well. Companies planningdelivery routes must consider the trade-off between the financial and environmental aspects of transportation. Efficiency of delivery routes is impacted by truck size and the possibility of dividing long delivery routes into smaller ones. The results of computational experiments modeled after real data from a Spanish food distribution company are reported. Computational results based on formulated optimization models show some balance between fleet size, truck types, utilization of fuel, carbon emission and production of noise. As a result, the company could consider a mixture of trucks sizes and divided routes for smaller trucks. Analyses of obtained results could help logistics managers lead the initiative in environmental conservation by saving fuel and consequently minimizing pollution.
Open Access
Integrating simulation and optimization: a case study in Pamplona for self-collection delivery points network design
(Cal-Tek, 2023) Izco Berastegui, Irene; Serrano Hernández, Adrián; Sawik, Bartosz; Faulín Fajardo, Javier; Estadística, Informática y Matemáticas; Estatistika, Informatika eta Matematika; Institute of Smart Cities - ISC; Universidad Pública de Navarra / Nafarroako Unibertsitate Publikoa, PJUPNA26-2022
The disruptions experienced by the processes in the last mile delivery during the SARS-CoV-2 pandemic raised the dilemma of up-to-date last mile approaches for Urban Logistics (UL) issues. Self-Collection Delivery Systems (SCDS) have been proved to be an improvement for all the players of the SC, providing flexibility of time-windows and reducing overall mileage, delivery time and, consequently, gas emissions. Differing from previous works involving hybrid modeling for automated parcel lockers (APL) network design, this paper brings a System Dynamics Simulation Model (SDSM) to forecast online shopping demand in the Spanish city of Pamplona. A bi-criteria Facility Location Problem (FLP) is solved by means of an e-constraint method, where e is defined as the level of coverage of the total demand. The experiment run considers 90% of demand coverage, in order to obtain the most complex network possible. The simulation and demand forecast was carried out using Anylogic simulation software and the optimization procedure makes use of the Java-based CPLEX API solver.
Open Access
Project and prototype of mobile application for monitoring the global COVID-19 epidemiological situation
(MDPI, 2022) Plonka, Julia; Sawik, Bartosz; Estadística, Informática y Matemáticas; Estatistika, Informatika eta Matematika
The purpose of this research is to analyze currently available solutions that help to monitor the global epidemiological situation, including travel restrictions, as well as proposing a new solution dedicated to users who want to keep updated with the current restrictions and COVID-19-related statistics. The analysis of existing tools is prepared from the perspective of practical usability for the end user. This paper consists of an overview of the tools and techniques of data visualization and demonstrates how to integrate them with practical business usage in a mobile application.
Open Access
Multi-criteria simulation-optimization analysis of usage of automated parcel lockers: a practical approach
(MDPI, 2022) Sawik, Bartosz; Serrano Hernández, Adrián; Muro, Álvaro; Faulín Fajardo, Javier; Estadística, Informática y Matemáticas; Estatistika, Informatika eta Matematika; Institute of Smart Cities - ISC; Universidad Pública de Navarra / Nafarroako Unibertsitate Publikoa
The rapid growth of electronic commerce is having an impact on the way urban logistics are organized. In metropolitan settings, the last-mile delivery problem, i.e., the problem regarding the final stage of delivering a shipment to a consumer, is a major concern due to its inefficiency. The development of a convenient automated parcel lockers (APLs) network improves last-mile distribution by reducing the number of vehicles, the distances driven, and the number of delivery stops. Using automated parcel lockers, the last-mile issue could be overcome for the environment’s benefit. This study aimed to define and validate an APL network containing hundreds of APLs with the use of an example made up of real case study data from the city of Pozna ´n in Poland. The goal of this research was to use mathematical programming for optimization and simulation to tackle the facility location problem for automated parcel lockers through a practical approach. Multi-criteria simulation-optimization analysis was used to assess the data. In fact, the simulation was carried out using Anylogic software and the optimization with the use of the Java programming language and CPLEX solver. Three years were simulated, allowing for comparable results for each year in terms of expenses, e-shoppers, APL users, and demand evolution, as well as achieving the city’s optimal locker usage. Finally, encouraging conclusions were obtained, such as the relationship between the demand and the number of lockers, along with the model’s limitations.
Open Access
Robots for elderly care: review, multi-criteria optimization model and qualitative case study
(MDPI, 2023) Sawik, Bartosz; Tobis, Sławomir; Baum, Ewa; Suwalska, Aleksandra; Kropińska, Sylwia; Stachnik, Katarzyna; Pérez Bernabeu, Elena; Cildoz Esquíroz, Marta; Agustín Martín, Alba; Wieczorowska-Tobis, Katarzyna.; Estadística, Informática y Matemáticas; Estatistika, Informatika eta Matematika; Institute of Smart Cities - ISC
This paper focuses on three areas: the first is a review of current knowledge about social and service robots for elderly care. The second is an optimization conceptual model aimed at maximizing the efficiency of assigning robots to serve the elderly. The proposed multi-criteria optimization model is the first one proposed in the area of optimization for robot assignment for the elderly with robot utilization level and caregiver stress level. The third is the findings of studies on the needs, requirements, and adoption of technology in elderly care. We consider the use of robots as a part of the ENRICHME project for long-term interaction and monitoring of older persons with mild cognitive impairment, to optimize their independence. Additionally, we performed focus group discussions (FGD) to collect opinions about robot-related requirements of the elderly and their caregivers. Four FDGs of six persons were organized: two comprising older adults, and two of the other formal and informal caregivers, based on a detailed script. The statements of older participants and their caregivers were consistent in several areas. The analysis revealed user characteristics, robot-related issues, functionality, and barriers to overcome before the deployment of the robot. An introduction of the robot must be thoroughly planned, include comprehensive pre-training, and take the ethical and practical issues into account. The involvement of future users in the customization of the robot is essential.
Open Access
E-learning as a factor optimizing the amount of work time devoted to preparing an exam for medical program students during the COVID-19 epidemic situation
(MDPI, 2021) Roszak, Magdalena; Sawik, Bartosz; Stando, Jacek; Baum, Ewa; Estadística, Informática y Matemáticas; Estatistika, Informatika eta Matematika
The COVID-19 pandemic had a huge impact on the learning and teaching processes, particularly in healthcare education and training, because of the principal position of the cutting-edge student-patient interaction. Replacing the traditional form of organization and implementation of knowledge evaluation with its web-based equivalent on an e-learning platform optimizes the whole didactic process not only for the unit carrying it out but, above all, for students. This research is focused on the effectiveness of the application of e-learning for computer-based knowledge evaluation and optimizing exam administration for students of medical sciences. The proposed approach is considered in two categories: from the perspective of the providers of the evaluation process, that is, the teaching unit; and the recipients of the evaluation process, that is, the students.
Open Access
Risk-averse decision-making to maintain supply chain viability under propagated disruptions
(Taylor & Francis, 2023) Sawik, Tadeusz; Sawik, Bartosz; Estadística, Informática y Matemáticas; Estatistika, Informatika eta Matematika
In this paper, stochastic optimisation of CVaR is applied to maintain risk-averse viability and improve resilience of a supply chain under propagated disruptions. In order to establish the risk-averse boundaries on supply chain viability space, two stochastic optimisation models are developed with the two conflicting objectives: minimisation of Conditional Cost-at-Risk and maximisation of Conditional Service-at-Risk. Then, the risk-averse viable production trajectory between the two boundaries is selected using a stochastic mixed integer quadratic programming model. The proposed approach is applied to maintain the supply chain viability in the smartphone manufacturing and the results of computational experiments are provided. The findings indicate that when the decision-making is more risk-aversive, the size of the viability space between the two boundaries is greater. As a result, more room is available for selecting viable production trajectories under severe disruptions. Moreover, the larger is viability space, the higher is both worst-case and average resilience of the supply chain. Risk-neutral, single-objective decision-making may reduce the supply chain viability. A single-objective supply chain optimisation which moves production to the corresponding boundary of the viability space, should not be applied under severe disruption risks to avoid greater losses.
Open Access
A multicriteria analysis for the green VRP: a case discussion for the distribution problem of a Spanish retailer
(Elsevier, 2017) Sawik, Bartosz; Faulín Fajardo, Javier; Pérez Bernabeu, Elena; Estadística e Investigación Operativa; Estatistika eta Ikerketa Operatiboa
This research presents the group of green vehicle routing problems with environmental costs translated into money versus production of noise, pollution and fuel consumption. This research is focused on multi-objective green logistics optimization. Optimality criteria are environmental costs: minimization of amount of money paid as externality cost for noise, pollution and costs of fuel versus minimization of noise, pollution and fuel consumption themselves. Some mixed integer programming formulations of multi-criteria vehicle routing problems have been considered. Mathematical models were formulated under assumption of existence of asymmetric distance-based costs and use of homogeneous fleet. The exact solution methods are applied for finding optimal solutions. The software used to solve these models is the CPLEX solver with AMPL programming language. The researchers were able to use real data from a Spanish company of groceries. Problems deal with green logistics for routes crossing the Spanish regions of Navarre, Basque Country and La Rioja. Analyses of obtained results could help logistics managers to lead the initiative in area of green logistics by saving money paid for environmental costs as well as direct cost of fuel and minimization of pollution and noise.